I was like, maybe they're right.
Maybe we should just sell.
And I remember having that conversation with Ben, which is he said hey, you can do whatever you want.
You can sell.
You're going to make a lot of money and you'll be super successful in life.
But you know, if you're like me, you're going to look back the rest of your life thinking, you know I missed that one shot.
That was the one thing I should have taken it all the way.
And now I'll never know how far I could have taken it.
Could have been.
So do you want to live with that or do you want to just have the money?
You know, I'll support whatever you want to do.
I really couldn't care less.
In 2016, when Databricks was on the brink, the board wanted a new CEO.
Co-founder Ali Ghazi was ready to go back to academia.
Instead of leaving, he took the job and turned an open source project into a $100 billion company.
On this episode of Boss Talk, I'm joined by Databricks CEO Ali Ghazi, alongside Ben Horowitz and Sarah Wang.
We unpack the 2016 crisis the Microsoft deal that changed everything and how Databricks built intensity without burnout.
We also talk about giving feedback that actually lands.
And why not?
Selling might be the boldest call a founder can make.
Let's get into it.
Excited to bring back Boss Talk.
This was a series that you guys did a few years ago on Clubhouse.
That was a big hit.
Yeah, we had fun.
It was Ben's idea.
Yeah, excited to bring it back.
So, in the spirit of Boss Talk, let's talk about the first time that you became a boss in terms of running Databricks.
Let's talk about the moment in 2016 when things weren't as smooth as perhaps they should have been and we were looking for a new CEO.
And Ben, you recommended Ali.
First of all, kudos to Jan for building the company originally and Ben investing and believing in us.
And then also, I kind of couldn't have done the CEO job.
Ben basically babysat me the first couple of years.
So short babysitting.
So I did know what was kind of wrong with the company, because I had been there for two, three years and I had seen from inside what we should change and what the issues were.
But we had an open source project that actually became very successful, thanks to those first two, three years.
Apache Spark became a worldwide sensation.
And we could pride ourselves on the number of downloads of the software.
And the Spark conference.
Yeah, yeah.
Spark conference.
Now the data and AI conference.
Yeah.
But the problem was that, as it is often with open source, is that everyone is just downloading the open source version.
Actually, your biggest enemy is your open source project.
The main thing you have to fight in the market is hey, why can't I just download the open source version?
Amazon is offering it.
The cloud vendors are just offering it.
I'm just going to use that.
So this was the biggest challenge that Databricks had at the time.
And we needed to do very serious aggressive pivots internally which were going to be very, very painful to lots of people, like to the whole ethos of the company internally.
And so I kind of knew that for almost a year.
So when I got the shot, that's what we started doing.
The strategy was like make Spark the biggest open source thing.
I mean, I can remember it on all the slides now.
And then Databricks would have the best Spark.
But Databricks never had necessarily.
We didn't do a lot to make it the best Spark or not differentiated enough.
And that was kind of the first thing Ali did on the product side.
And then he hired Ron Gabrisco, which that was transformational.
Because that kind of dragged the company into the world.
Obviously, that was the right decision and paid off.
Zooming out, Ben, you've worked with and you know all the great CEOs of RRN and worked with them.
Where does Ali spike and where are his superpowers as a CEO, as a boss, that have helped contribute to the impact?
I mean, Ali's really good.
So I always rate CEOs as okay.
If I was running that company, would I do a better job or a worse job?
And with Databricks, I do a way fucking worse job.
So he's good on many, many dimensions.
So I'd say, first of all, he is a real technologist like, not a pseudo technologist like his competitors.
I'm sorry.
So he really knows the product.
He understands the product strategy in detail.
He also ran engineering before he was CEO.
You know, mostly what I worked with him on the early days was just, okay, go to market and BD.
And he's really good at both of those.
That's where we had to catch up.
You know, Stuff Like had an amazing go to market.
And then we needed a big deal with kind of big partners.
And I remember, I mean, I...
I got him like a little BD tutor.
John O'Farrell, who did a nice job, came in and kind of taught Ali about how you structure a deal, how you do things.
But he learned everything so fast.
And then probably the thing that he does that I wish I could get all our CEOs to do is he doesn't hesitate.
He trusts his eye.
Like he'll see something and he doesn't know if it's right.
And so if you look at the strategy changes Databricks has had, one big one was building a data warehouse.
That is a pretty big swing and a seemingly like quixotic, insane idea, given where they were.
He's paranoid enough that he knew that could be an issue.
And then he trusted himself enough to go, get deep enough to decide whether to do it or not, as opposed to, you know, ignore it.
These guys are trying to kill me.
I don't want to see it, which is what a lot of CEOs do.
And so that kind of thing.
But there's a lot of elements to that job.
It's a very complicated job.
Ali talk more about the journey, about evolving from an academic, a technologist to someone commercial.
It's a journey our CEOs go through.
Talk about what it was like for you and in the context of what others can learn from it.
So we were in academia, so we were scientists.
And then, you know, I led engineering and product.
So you got to learn how to build a product and get product market fit.
And then I became CEO afterwards.
Each of these has different sort of challenges.
I think that in all of them, the thing that is in common is that you really have to understand and be extremely good at the task at hand.
And so number one, admit that you don't actually know everything about the job.
So A, first step of anonymous alcoholics, admit you have a problem.
Admit you have a problem, okay?
And then number two, be a student and learn everything you can about it, right?
Go all the way down to the details and try to learn from the best.
And then work your butt off.
You're nothing.
You're zero, right?
You know nothing about writing reliable software.
I would say that was the same thing.
I tried to learn.
I tried to network with the best heads of engineering, best heads of products.
I tried to read every book.
I got as much as I could out of Ben and Mark.
I read all of their blogs, all of their books, everybody else's.
But then you do search.
Search firms are really great at getting you to meet who's the number one product manager by reputation in the market right now.
Can you get 30 minutes with that person?
Just sit down.
They're not going to join you because your company is too crappy and too small.
Can you get 30 minutes with them?
Can you get a dinner with them?
Can you get a breakfast with them?
And then just ask them lots and lots and lots of dumb questions and they'll tell you.
They'll happily just tell you like, hey, here's how I do it.
The other guys are wrong.
And then they'll give you a playbook and you can go compare it.
You can go to the next person and say, hey, this is the playbook I heard from.
It's like, no, no, no, that's totally wrong.
You don't do it that way.
Here's how I do it.
And then very soon you learn enough.
And if you really have grit and you work hard, you're going to be able to do great things.
That's about you yourself.
But also, if you hire a great team, because as a leader, you alone can't do much.
So can you hire the best people out there?
So that's also part of that.
Do you know what great looks like?
Have you interviewed all the best people?
And then can you now sell them and get the best people to come work for you?
Once you start assembling a team of excellent people, then they will uplift you.
This is a managerial leverage that I learned from Ben, which is from High Output Management by Andy Grove.
But it's basically, are they so great that...
You're learning from them.
It's like Ali was a great head of engineering, but actually he was a great head of engineering because the people that worked underneath me were doing amazing things.
And I was just standing on their shoulders.
So you just have to do that.
And you have to instill everybody else to do that recursively, so that you end up with a just amazing killer team.
And you got to continue doing that.
Now you have to okay.
For engineering it wasn't actually that hard because I had written a lot of software, But now you're CEO.
So now you have to do that for marketing.
You have to do that for sales where they were super helpful because they had done it with LoudCloud and Opsware.
So they knew how to build a B2B machine, how the game was played.
But you have to do it again.
But now you're doing it in a field where you're really clueless.
And also probably all your instincts are wrong and your intuition is completely wrong.
So can you be clairvoyant and see the truth?
Or do you want to lie to yourself?
And that's where I think a lot of founders make mistakes.
Like they'll do well in their own archetype.
When they have to step outside of their own archetype, they make a mistake.
They hire people that are like their own archetype in other roles where that could be lethal.
By the way, that's how we started Databricks was.
I think everybody was a PhD in computer science who was running anything.
Including sales.
Yeah.
That's probably the number one mistake.
Is You just go okay?
Well like I'm an engineer, so I want a sales guy who can talk to me and understands engineering.
Well, that's not a really good criteria for sales guys.
So those kinds of things, he just learned faster than most other CEOs who are in that position.
And then he's taken a lot of stuff that I know how to do, and he's done it much better.
So one thing that I'm good at is, rather than telling somebody that's stupid and hurting their feelings or so forth, I'll ask them a really fucked up question.
Actually, I did it in a board meeting.
I said, well, could you help me with the math on this?
Because I don't understand the math.
Actually, it was worse.
He said, help me with the, I'm just trying to understand basic math.
You have all these numbers on the slide.
And if you said that your conversion ratio is 5, but I can't divide any of those two numbers to get 5.
And then the person freaked out.
Don't freak out.
Just tell me which of the two numbers do I divide to get 5%?
Because I've divided all of them and none of them is 5%.
Am I going to be fired?
So he does a much better version of that, which is, if somebody's really really screwed something up or messing, he'll go.
How do you think it's going?
Since he told me that, I was like, oh, yeah, that's a better way to do it.
That's even better.
So, yeah, he's a very good student.
Can I riff on that?
You know, there's this book called Radical Candor and I think people take it too far and they misunderstand it and so on.
But I think the essence of that book is that if feedback, if are you criticizing me?
Are you saying I'm stupid?
I can't do the vision?
Because my point is not about the 5%.
I was trying to make a different point.
And now you're just, this is a cheap shot.
And now I'm like hurt.
And I think, by the way, I think you're wrong.
It's not five.
I said six and a half.
So are you criticizing me?
Or is it like, no, no, no, I'm here like to help you.
I can like not help you.
But if you beg me for help, maybe I'll help you.
So which of the two modes?
So if you can get people into the mode of, oh, wow, I'm like being helped.
Like they're helping me and I'm going to get further ahead in my career and I'll be more successful.
Please, no, no, no, please don't leave.
Come back and tell me more because I'm taking notes here.
So if you can flip to that and I think a lot of feedback can be recast into I'm just here to help you, but feel free to completely ignore this advice.
But if you want to be really successful, if you want to get that job or if you want to get that project next time, if you did it this way, then you probably would have had a higher probability of getting that, but I don't care.
You do whatever you want.
And then people are much more receptive.
They're like, no, no, no, please, I want to know more.
Yeah, yeah, yeah.
Well, and then just the frequency of it I think helps a lot too, where...
If I see you once a year at your review and I tell you what's wrong with you, you're going to be offended, no matter what it is.
No matter how wrong it is, no matter how correct I am, it's going to be offensive.
But if every day, if I see you doing something I don't like, I go no, don't do it that way, do it this way.
Then you get desensitized to it.
And so I think the mistake a lot of particular engineers make is they just don't say what they think when they think it, because they're afraid of hurting someone's feelings.
But that's how you save their feelings because they're used to you.
You're always doing that, and you're doing it with everybody.
They see it.
They're like, oh, yeah, fuck, Ben's an asshole.
He's, like, always doing this.
But that's how he is, and that's how we work and it's no problem, as opposed to the hammer and you try and put it in a shit sandwich.
Oh, you do this really well, but this is all fucked up.
This is good.
And people are like well, so like now in my written review, you're telling me that for the first time, this is all fucked up.
Fuck you.
This is very common.
And you can see this in the industry that the extreme version of it is like they get fired.
Right.
And then head of HR talks to them and they're like, you know, do you see this coming?
It was obvious, right?
You knew it.
I had no idea.
Yeah.
I was like, wait, you didn't get any feedback on this?
No.
I only got thumbs up all along for like a whole year.
So I'm in shock.
This is super common, right?
So maybe on the topic of managing talent, you have this incredibly high intensity culture at Databricks.
And there was this thread recently in our CEO thread where they asked everyone.
But you had a great response on hey, we have 50 people.
How do we scale?
We have this culture of 996, right?
You work nine to nine, six days a week.
How have you scaled that intensity well into 10,000 employees?
I think start with, you know, setting the tone at the top.
If you're the hardest working person you know, kind of everything will take care of itself from there on.
If you're not working hard, it's very hard.
I mean, if you have, you know, it's a double standard.
I mean, Ben has a whole book about that, which is you know.
It's basically you know what you do, is who you are.
Is the whole title of the book right?
So it's like if you are working extremely, extremely hard, the rest of the organization is also as well.
You know, are you calling people at 9 p.m., 10 p.m.?
Are you working weekends?
Do they expect you?
Not that you expect them and you're going to be angry and yell at them if they're not dropping everything for you.
Not that.
But the fact that they just know that Ali is working 24-7 and he's working seven days a week and he's working at 11 pm or 2 am or whatever it is, I think that gets a lot of it done.
The second thing I would say is you can vet for this when you hire people.
And the easiest way to vet for it, Because you know you got to be careful with it, because the people who say they're going to work the hardest are not the ones who work the hardest.
It's the opposite.
Yeah, 100% true, right?
So the best way to vet for this is to the back doors.
You know, ask people.
People don't, if I ask someone, you know, hey, how was Sarah?
Like, did you like, was she great?
They're always going to say, yeah, she was great.
Right, mm-hmm.
But they're going to be much more honest if you ask them like hey, how much does she like grind the midnight oil?
Is she like, and they'll tell you right away.
It's like, oh my God, she works like crazy.
It's like, you know, she's, I mean, I think she has a good balance.
You know, you can like suss that out very easily.
From back doors references.
You can people remember the people and they'll just offer it up and say oh, that person was like nuts.
They were like working 24 seven.
So I think that way you can get people that are hardworking.
By the way, I don't want to overemphasize.
I don't think everything is just work harder.
You know, you have to also work smarter.
And I think that you want to make sure that it's sustainable.
I can work insanely hard.
I'm motivated.
Everybody has a different threshold for how hard they can work.
I don't think you want a culture where people are burning out.
I think you really should avoid that.
In fact, you know, at Databricks I'm very often going in and saying hey, this team, like you know, your scores are really bad on work-life balance.
Like, what are you doing about it?
Or you guys should take several days off or you should do some offsides or do something.
Like, we actually go in and if we see that there's some groups...
And other groups at Databricks, you know, their work-life balance scores are like 100%.
They're like, you know, slacking off.
You know, so then it's kind of the opposite.
But I do think that you can kind of up for that.
And I think that also setting the expectation.
You know, I would say you know.
One of my competitors, Frank Slootman, wrote a book called Amp It Up.
It's a great book on how you get... you know, execution into a company.
Like getting a high-performance culture where everybody's always trying to excel and do better and better.
Sort of that kind of culture into a company.
That's a good book if you want to just study.
And he's doing it at scale at bigger companies.
So I think that's highly recommended reading as well.
Yeah, and I think...
You know, a lot of it at his scale ends up being things like organizational design.
Are people feeling like they're having an impact?
If people are feeling like they're having an impact and they're good, then they'll work very hard.
But if you're in some kind of weird three-legged race that the CEO has constructed where everybody's got dependencies on everybody else, It just doesn't matter.
You know like you'll just have a lot of people go, like I know, if I work hard it's not going to make a difference.
So, like, why would I do that?
And, like, you can't overcome that with rah-rah and, you know, lead by example or anything else.
Like, that's just fundamental to how it is.
And you see, in like in any company of any scale, you know, even at our scale, like there are some groups who – really can have impact and work extremely hard and then groups who have lesser impact will work less hard.
And you just see that.
You know people who are motivated and they feel excited about work and they see the impact that they're having.
They're going to work way, way harder.
Versus.
If you're demoralized and you feel like it's not going well, I'm not having impact, I don't have any autonomy, then you know you're not going to.
You just don't want to.
Even you're like kind of depressed, sitting down working.
I do think there's one thing here where leaders can really help, which is to make your team feel like they're winning and that they're doing a great job.
Like you can ask more from people.
But if I feel like hey, I'm losing and everything we're doing is wrong and I'm putting in all these hours and it's stupid, like there's like what's the point of this?
Then people don't want to work.
So I think it's like feeling like we're winning, like we're the winning team.
We're winning like you know and wow, they're expecting more from me.
And, you know, so then I think you can get, you need that motivation in people.
Yeah, yeah.
Which is why, by the way, the hard job is, When you aren't winning, to get the output, like particularly in Silicon Valley, because you know you're battling attrition, this and that, and to get things on the right track.
That takes a whole different – kind of level of technique and storytelling and show you how you could be winning and all that kind of stuff.
That gets very, very complicated.
We've both done that, right?
Yeah, yeah.
There's been phases in our company's lives where we weren't winning.
Yeah, yeah.
I mean especially, you know, the story you had in Hard Thing About Hard Things, which is probably the best business book I've read which I read, by the way, before starting Databricks and it influenced us a lot.
Yeah, that's the difficult...
That's such an important point because even if you're winning, people got to feel like that.
But if you're not winning, getting them to feel like you're winning is...
We have a path to winning.
Yeah, we have a path to winning.
You know, and it's like rock solid.
It's going to work.
But it would demand sacrifice from all of us.
And there is no feeling as good as when you're not winning and then you get it to winning.
Like that's the best feeling.
You can't replicate that.
Once you're super successful, you never can quite get that feeling again.
Yeah, that's true.
But you also never feel that horrible pain again.
Well, it's easier to be the underdog in some ways, right?
You know, you have nothing to lose.
In some ways.
In most ways, not.
Well, I want to explore this leading from the top, because that was kind of the first thing you started with.
We actually hired an ex-Databricks employee to A16Z.
So we have some inside scoop on your leadership style.
And one of the things he said was you have this and Ben sort of touched on this too but you have this amazing ability to be strategic, help your team focus, but you're also very in the weeds.
Like you're giving product feedback, you respond to emails super quickly and you're product launch emails, no matter how small they are, you'll respond.
Congrats, which he found hugely motivating.
How do you do all that?
And where do you fly high?
Where do you fly low?
Yeah.
By the way, I respond even to progress reports on all those products and I follow them in detail.
Every one of them.
I try to respond to every product.
Insane.
Respond.
But look, I think this is if you're just going to fly high and give high level like inspirational speeches, and then you know we'll trust them, we'll delegate to people.
It's not going to work.
So my way is, you know, you got to get in the weeds.
You got to understand.
This is back to what I said at the very beginning.
Like, how do you become great at the head of engineering?
How do you hire a great head of marketing?
The only way you can do that is by being really excellent at it.
So you need to study the game and become the best.
So I try to stay tuned to all of these things.
There's this quote, if you do everything, you will win.
And then the question is, have you done everything?
Exactly, exactly, exactly.
So, yeah, so, you know, you just, it takes a lot of effort.
You know, you need to learn all your keyboard shortcuts.
But I think that's, you know, people feel motivated that, hey, I have like direct relationship.
You know, we used to say we used to have one of the culture principles used to be hey, be a co-founder.
And we don't want to have any employees at Databricks.
We just want co-founders.
And the key point was like, hey, you're kind of the owner of this company.
You're not just a renter.
Come here and yeah, we can talk about it.
And you can suggest an idea.
You might have just joined and you're straight out of school.
You might have a great idea for a product.
Tell me about it.
You know, I'm happy to push it.
And so it's making people feel like they have an impact and they're inspired.
Back to Ben's point.
Then it's going to be much more exciting for them, right?
Than following some bureaucracy.
So I don't follow the bureaucracy, basically.
I go talk to anyone I like.
I try to go to the person that is actually the closest to the work that's being done at any given time.
But there are some tricks and rules around how you do that without breaking the whole organization.
So you can't just willingly talk to anyone.
But yeah, that's part of it.
Yeah, listening and giving direction is very different on that.
If you give direction...
You can cause a lot of chaos.
But if you go talk to people, you listen to understand the problem and then send it back down the chain of command.
It tends to work very, very well.
But look generally, if you're a CEO and you don't fly low and fast, It's going to be a mess, because you never get the truth, because the truth never makes it to you, like through your people.
Like if I go talk to Ali's executive staff about what's going on in their organization, or anybody's first of all, they're going to spin it.
Second of all, they don't actually know.
And so like you can't – you need to help them debug their organizations because –
They got a million things going on.
They're also kind of going to the problem, going to the bottleneck, trying to figure out what's happening.
And so, like, it's just a very unreliable source of information.
All the knowledge in a company is with the individual contributors that are doing the work and the customers.
Like, there's no...
There's no knowledge with the people who are talking to you as CEO who are on your staff.
That's not the way information moves.
And so you got to be... Now, he's like super fast, which enables him to go super low.
But, you know, in any given time...
The way to think about it as a CEO is it's not like you're spending the exact amount of attention to HR as you are to the key engineering project as you are to the key kind of sales, competitive deals.
You have to...
You don't address everything evenly.
You can never do that.
It's just a bad idea.
Now, you'll probably get to everything eventually, but you're not spending the same amount of time on every single department.
The org chart is not the way that company works.
It's just a communication architecture.
Yeah, I think the best way I would say it is like it's kind of like a T and one of you broad, and then you have the leg that goes down and goes really, really deep.
But you want to do that anchoring.
And the key thing is to have a really good priority order of what's most important and kind of drop everything else.
Like, you know, you drop that T and go really, really low.
Like it might be HR.
I might be deep diving all the way down to HR, looking at our HR handbook, our policy, everything.
Like, who was this person?
What happened?
Why is this happening in that group?
What's going on in that group?
What's the culture in that group?
What happened here?
You might want to do that.
It might be existential for a company, as we've seen.
Some companies went under because of HR problems. right, or ethical issues that were going on.
So I think having a really good priority order is really important.
I think some execs, like, they just want to have a perfect ducks in a row.
I have my weekly one-on-ones.
I have my weekly staff meeting.
I have my weekly this.
And then I do this.
And then we follow the rules.
And then we do all of this.
And then that's, like, just, like, the top part of the T. And then there's nothing that goes deep.
And that's the issue, I think.
Yeah, over-systematizing or making it, like, symmetrical.
You don't even...
You don't have to have one-on-ones with the same frequency of all your staff.
Or like some of them, you know, like you can meet very seldom.
Like everything is different.
Every part of the company is different.
You may need to meet with somebody every day.
Yeah.
And then other people you know you can meet once a quarter for now, because it's just not that serious.
And you can't get caught up in making everything fair and symmetric, particularly like your staff.
They got to be able to deal.
Yeah.
And this is actually the biggest conversation that I had with Ali early on is like If they can't do it, they can't do it.
That's it.
It's a wrap.
Yeah, yeah, yeah.
Don't try and fix them.
They can't be fixed.
It's not going to happen.
And, yeah, it's a sad lesson, but an important lesson.
I want to turn the conversation to an area that Ben was saying you had to catch up on, at least in the beginning, which is the BD deal-making stuff, which is interesting to me just because I think of you as a consummate deal-maker.
I feel like you're playing chess.
Everyone else is playing checkers.
I want to go back to 2017 with maybe one of the first game-changing deals that you guys did, and that was the deal with Microsoft.
Can you guys talk a little bit more about how that deal came about, anything you'd do differently?
And, by the way, founders still to this day ask us about it because it's sort of a model for how they'd like to do deals.
Yeah.
Maybe I should start by saying that you know we had tried to get close to Microsoft for a long while.
I think Ben had told us you need to.
That's an important partner because they have the biggest distribution channel.
You know, today they have 60,000 sellers.
If you can unlock that in any small way, it's going to be a game changer for you.
And I had been CEO for a year, so I'd been trying hard to get in there.
And many, many people offered me, you know hey, so here's.
I actually know Satya, so I'm going to get you introduced.
And I got multiple introductions to Satya.
He just like either never responded or just cc'd his EA and it went into his EA loop.
You know like we're still trying to find time.
He's been so busy this last six months, you know so.
But then then he had a meeting with Ben, and I think it was here actually at A16Z and and And they actually just talked and I was not actually in the loop.
And then he called me up and said, hey, I talked to Satya and I think he's excited.
He wants to do this.
And I saved the email.
So Ben introduced me to Satya.
And this was, I think, 3 or 4 a.m.
I was like in New York.
And the email went to Satya.
And then Satya added like four or five people to the email thread.
And then they added four or five people.
So like within an hour, I had like 25 emails in my inbox.
And suddenly all these people that were not responding to my emails from Microsoft right after Satya cc'd them and cc'd the next person.
They were all like hey, I'm clearing my calendar.
Would love to meet you.
Do you have any time in the next two days or three days or, you know.
But really kind of the original pitch of what's the give and get was Ben and Satya at A6NZ.
And they kind of figured it out.
And I was not actually even there.
So we had some luck, and then Ali did a couple of things that were, or quite a few things that were very, very effective.
So the luck was, at the time, deal with big companies, there's always a timing element.
And there was a company called Hortonworks that had a deal with Microsoft to provide some similar kind of functionality And they were basically putting a gun to Microsoft's head, saying like you pay us more money or we're going to pull our product.
And they were on-prem and they were in cloud.
So it was like a big mismatch also.
Yeah.
So it was a real, so Microsoft was like super pissed at them and wanted to stick it to them.
And so that was, you know, so you have Satya going like, I think this company is interesting.
And then this ground level thing going like, we want to fuck these guys.
Yeah.
And that kind of opened enough of a door to get it going.
But there were.
So, like one of the most important things in the deal was, which you know, and John O'Farrell really emphasized this for both of us was look, you got to get them to put enough, They're such a big company that they're going to lose interest many times.
So if you don't have them write you such a big check that somebody in there is going to get fired if it doesn't go well.
It doesn't matter if you get the deal.
You're going to lose the deal.
And so what we did is we're like, and the technique that we had was, okay, give us a forecast.
Like, we're a little company.
We can't afford to do this deal.
You know, we can only afford to have one partner.
So give us a forecast of what you'll do.
Yeah, because our engineer are busy.
They're going to do this integration.
That wipes out 12 months of our roadmap.
We don't have anything else.
You guys have like many thousands of engineers.
So this is, we only have one of these.
Yeah.
So we, you know, whoever can sell them.
We think you can sell the most, but we don't know like what's your first.
So, you know, like kind of challenge their kind of manhood a little bit.
And so they come out with this big ass forecast and we're like, okay, great.
Just give us a little portion of that.
It was a huge deal.
It was a lot of money.
Yeah.
And then Ali said look, You know, when we got all the way down to the deal, he was like if I don't get this number, Ben's going to fire me.
And so can you help me out?
It was a very interesting dynamic.
So you know, John O'Farrell had strategized with us and told us that you know they have to do a big pre-commit because then they have skin in the game.
Otherwise, they're just going to forget.
They'll do like the PR, but then they'll forget about you.
But then when we were trying to get that from Microsoft, I remember I was talking to Takeshi Numoto, who is one of the main brains at Microsoft, one of the key strategists there.
And his thing was, I don't want to give you a big commit because you're such a small company.
I'm worried you take this money and you get drunk off of it and you're not going to do anything afterwards.
And so I had to really convince him that, no, I'm extremely hungry.
Like, there's no way.
Like, I will continue to have crazy appetites.
Don't worry about it.
So both sides were kind of worried about different things.
They were competing with AWS.
They had a gap at the time.
And we had a great product.
They have an amazing distribution channel.
So, like in these BD deals, there always has to be a give and get.
That actually is kind of commensurate.
And this is why most of these deals fall apart and they don't work.
There has to be something that you as a small player can give that they don't have.
And usually you don't have anything to give them.
Usually I find all these small companies show up and they come, for instance, to Databricks now and say oh, we'd love for you to partner with us.
But what am I getting out of it?
Right?
You don't report to me.
I don't report to you.
So the moment we've closed the deal, if it's not good for me...
Neither of us will just do our side of the bargain.
So there has to be something in the deal, dynamics in the construct, that inherently is extremely beneficial both sides.
There has to be a trade that makes sense.
Microsoft really wanted that product.
We really wanted their distribution channel.
And then the other thing that I think a lot of entrepreneurs don't understand is any big deal of that size.
You lose at least three times before you win it.
And we lost that deal.
Ten times.
Ten times.
And, like, including, like, the day before we were supposed to launch it.
You know, the antibodies came out of the company, and Ali had to fly up to Redmond and sit there.
There was one engineer that just said, not doing this.
This is not going to go.
They actually put a guy in place at Microsoft who was actually super, had a great reputation, but he was a builder.
So he just had huge problems with this.
It's like, this is not a product I built.
Why would I make this successful?
So yeah, usually there's many times.
So if you don't have grit, those deals will die.
Because this deal died multiple times, as Ben said.
It was completely over.
It was completely blocked by some exec that said, absolutely not.
I'm blocking it.
It's veto.
It's over.
And no one wanted to overrule him.
So you have to go in there and work.
And the only way we did it, they call it the nerd bird.
I would take the, you know, SF Seattle flight up there.
I was up there so much.
I knew all the buildings, all the rooms, everything.
So you just have to spend time on the ground and talk to as many people as possible and sort of influence that organization from within.
I will say look, you know, with all the difficulty of the deal, and you know, and Microsoft being Microsoft, they've been as good a partner, as not only we've had a Databricks but an entire portfolio.
I mean, they've really, you know, lived up and delivered uh, what they said they would do, which is I.
Yeah, they've been fantastic with us.
This was around the time where Satya had taken over and you know he was giving to everyone at Microsoft the book Growth Mindset or Mindset, which is about growth mindset.
So there was this kind of aura in the air that, you know, we should try.
Like, let's try to make things happen.
Let's have a growth mindset here.
Let's see, is there a way we can partner?
So this would have been impossible five years earlier.
So it's kudos to Satya and they put us on the map.
And he's been a great partner ever since.
You know, whenever there's been issues, they always resolve it.
So, you know, We are very thankful.
We wouldn't be where we are without them.
Yeah, just amazing.
Amazing, really.
I want to open up the conversation to deal-making more broadly.
Now that you're not a small company anymore and you're a big company making acquisitions.
You know Tabular Neon Mosaic, just to name a few.
What is sort of your approach in terms of when to build versus when to buy?
How do you think about acquisitions more broadly?
Yeah, I mean what we try to not do.
So let's start with a simple thing is a lot of companies, especially at scale, they'll buy revenue.
So they'll look at a company.
They'll say hey, this company is this size.
We'll just buy that company, we'll put more salespeople on it, then we can accelerate the revenue.
We're buying that revenue and that's how they're doing it.
We're not doing that.
You know, what we're really doing is number one.
We spend a lot of time with the team and the founders.
So we're trying to see, hey, can we build together?
Like you come here and you build together.
That's very different from that buying revenue model.
The buying revenue model, oftentimes you part ways with the CEO from day one.
Like you can see the big companies, They literally have a plan.
Like I have.
You know, I have some execs that come from these big companies to say hey, our plan usually is to part ways with the CEO.
Like you make a deal and the CEO can leave.
And then, but also the key people in those companies quickly leave, all of them.
Like at the top management, and then you know you keep promoting the people from below that couldn't get promoted before.
And then eventually you bring in your own people to take over the company, and then the company is dead.
There's nothing left of it.
And there's no integration between that asset that you bought and the platform that you have.
So to avoid all of those, can you get people that really feel like they're your co-founders?
So we spent just enormous amount of time with who were like the company, right?
Who are the founders?
How do they work?
Are we culturally the same?
Spend time with them.
Do we get along?
Do we see the world the same way?
You know, are we going to click?
Are we going to do this together?
Are we going to be able to build in the next five years?
So that's where we spend number one.
Number two, we spend a lot of time on the product.
You know, what's the product experience?
How would we integrate this?
What would it look like?
How much can we, can we rewrite most of it?
Can we not rewrite it?
What's the, what programming?
I always ask this and people are like, that's such a dumb question.
I say, what language did you write it in?
Why do you want to do that?
What does that matter?
No, because we're going to integrate the code bases, right?
It's like the build systems won't work.
It's not going to even compile.
So a product is something we spend a huge amount of time and talking to customers, understanding what the excitement around that product looks like and how the integration would look like.
The last thing we do is we'll look at the financials.
You know what's the revenue multiple and you know how much can we grow it and what's the three-year plan, five-year plan and so on.
And I feel like big companies, corporate departments do it exactly in the reverse order of this.
They start with hey, the revenue is this, but we could accelerate it and the multiple is so low and, like you know, in my Excel sheet here, this makes perfect sense.
You know, and then second, they go to like, hey, is this a good product?
And then lastly, like, hey, how do we convince these knuckleheads?
I mean, we probably don't want to have him here, but we've got to pay him off somehow.
So I think, you know, thinking about it that way, you get more longevity out of it.
Yeah, and this really comes.
That's going to mean multiple SE forces, multiple post-sales things, and your entire sales efficiency is going to go through the floor.
And because they have a keen eye on that, everything they buy ends up looking like a Databricks product.
And that work is going in.
They're not just selling some shit to get some money to go on a corp dev thing.
And I would say so many, like when you bring in a professional CEO.
This is what they screw up, because they don't understand that yeah, engineering goes.
Yeah yeah, we can take it on.
There's another set of engineers.
We don't care if they work on that, blah, blah, blah.
And engineering gets less efficient too, but it wrecks the field.
And then the customers hate it.
Customers hate it.
Yeah, like, okay, I've got to learn another access control model.
I've got to do this.
These are not things anybody wants to be part of.
Yeah, 100%.
Yeah, it's the go-to-market side that you're worried about, that experience that those customers will have.
They're going to come back immediately and say hey, we were already upset about these things before the acquisition.
Maybe you can fix them now.
It's like, no, actually, several of those people actually quit.
And now we're going to just work on integration.
And that thing now got pushed out another two years.
So you don't want to be in that situation.
So there's a lot of companies that do that.
And by the way, what they're doing works revenue-wise.
They are getting the revenue.
They are getting the stock swap works.
Like, you know, if they're multiple of the companies.
It's in a creative deal temporarily.
Yeah, it works.
And then the first year you get the bump in the revenue and you get a second year boost in revenue growth as well.
So financial engineering actually works great for those companies.
It's just long-term.
It ends up being like, you know, A bag of crap that doesn't work together.
And it affects the brand.
You know like one of the things is one of the reasons Databricks is so powerful is all their customers want to buy all their products because they're like we know that's the best software we buy.
And as soon as you start chipping away at that with these financial strategies, like you can't get it back, because the reputation is every customer's experience.
There's no marketing through that.
It's the best software because it was written by the engineers and built by those that were the best, including the acquisitions that we got.
They were phenomenal people that came in and they continued.
And since we gelled, they continued building it.
So that's why it's great.
It's like the, you know, so we pay a lot of attention.
That's like back to the, you know, who are you getting into your company?
Yeah.
Yeah.
Oh, that's the other thing, right?
Like...
You can buy something that's got a lot of sales where you're downgrading your whole company.
Ross Perot actually wrote about in Citizen Perot his biggest fear, which definitely came true, was he built this elite thing at EDS and then they would actually acquire IT departments.
And he was like, They're going to absorb us, not vice versa.
And that does happen.
Yeah.
There is one really good company that... Well, one really successful company that we never acquired.
And I always vetoed it whenever it came up, because I just think that the quality of their employee base is not great.
And I didn't want it to dilute Databricks.
Otherwise, from every other angle, that deal always made sense.
And I always vetoed it because I felt that it's just...
They're all going to quit or be super unhappy.
Let's just not do it.
Yeah.
It's also why I like merger of equals.
Because the cultures aren't equal.
The people aren't equal.
And what made you feel that way?
You just spent time with them and they just didn't exude through Databricks culture?
Well, I mean, it's, look, it's like with everything else.
Like it's like when we were grading students at the university.
It's like okay, the rock stars are super easy to find out.
So they're like there.
And then the people that are really, really bad, that's like, it's not hard.
And then there are people in the middle that's in the gray zone.
This was a company that was you know.
I feel like the talent is not phenomenal and you don't need to be a genius to know that.
And then there's some startups, you know, immediately.
Like you know okay, these guys are Olympiad winners and they're like phenomenal and they're like executing like crazy and they have a track record.
So I don't think those are that hard.
And we try to hire these and this is the one that I vetoed.
The hard part is what do you do with the ones in the middle?
That's always where you spend all of your energy trying to suss out.
Like, you know, okay, they're not stellar, stellar, but maybe they are.
Maybe they just didn't have, maybe they didn't have the go-to-market, they didn't have the funding, they didn't have the support that they needed, and so on.
Maybe they could if we give them a chance.
Or maybe they're just mediocre.
And that's where you spend a lot of your time.
But you've got to spend time with them.
You have to interview all the people.
You know, you have to have your people interview all the people.
This can't be an Excel sheet exercise.
Yeah.
And Silicon Valley has a lot of lopsided companies.
So you know, you'll have a great engineering team and a bad company, because it's like you know bad leadership, bad go-to-market.
You also can have Like guys who can sell anything with a ridiculously like poor engineering team and they can just sell it.
And, you know, you got to be very, very careful about that.
Actually our you know our CRO at Databricks is you know he came from a company that you know he'd sell anything.
He was selling SFTP, secure FTP, which is free.
And he was selling it for a lot.
That's how you know he's good.
He was selling it for a lot.
He was making a lot of money.
He was saying, you know, the electronic medical health records, you know, how important are they?
If they got dropped, you know, how much of a risk is it to your business?
Well, this is secure, FTP.
You made it to be secure.
Yeah, and somebody grabbing that file.
He's good.
Yeah, the only thing I'd add too, is this strategy is probably making you more attractive to the people you want to acquire too.
They don't want to sell if they're going to get fired right away.
Yeah, for sure.
It's very competitive.
Yeah, 100%.
Yeah.
I mean, you know, there's also a reputation, right?
People know, like they'll look back and say, okay, what happened to your previous acquisitions?
Yeah.
You know, is there a huge fight and everybody's quitting left and right?
Or, you know, do they work out?
You know, how are you taking care of those people?
You know, what roles do they have?
Do they have influential roles in your company?
You know, that's also important.
So you're setting a precedent.
You're setting a precedent in many, many ways with acquisitions, M&A.
You know deal dynamics, the price, the you know when you go through, the lawyers come back and that's you spending all those 20, 30 days doing the definitive agreement.
Every little thing you agree to there is a precedent for the next deal.
Yeah.
Yeah, totally.
Maybe actually just to turn.
So we're talking about Databricks as an acquirer.
If we go back in time again to maybe a moment where you thought about selling and maybe that you know you didn't actually seriously consider that.
But I wanted to actually just sort of quote this infamous email sort of circulating our firm, that Ben sent to Ali.
Yeah, Ali brought it.
I had forgotten about it.
He brought it up at a board dinner.
And I was like, oh, shit, I said that.
And actually this was not pertaining to selling the company, but it was, I think, selling a candidate right.
And you talk about hey Ben, can you sell this candidate on the fact that it will be worth 10 billion, maybe 20000?
Yeah, because the candidate was worried about the company getting sold.
Yeah, he wanted to have a double trigger because the company, if Databricks sells and they fire me as a salesperson, what equity am I going to get?
So give me double trigger so I'm protected.
If we get bought and I get fired, I vest all my equity immediately.
Yep, exactly.
I'm like thinking about Ben's tone in this.
You are severely underselling the opportunity.
We are Oracle in the cloud and we will be worth 10x what Oracle is.
But what was your reaction when you when you saw that?
And did that give you more fortitude to not sell the company?
So Ben's crazy.
I think the first thought was exactly Ben's crazy.
But no, I think both Ben and Mark always kind of pushed us to think bigger.
I remember we did the pitch at A16Z for, I think, our series D, which would have been around 2017 or so.
And the question was asked, you know, what's your biggest bottleneck?
And I said, biggest bottleneck is hiring.
I said, okay, well, Who are you losing to?
And I said, well, it's Google.
It's the Fangs.
And the response I got back was, well, you need to just add the Databricks to Fang.
It needs to be FangDB.
With a straight face.
And my reaction was I laughed.
I literally said, oh, yeah, yeah.
I mean, this is not serious.
It's like, yeah, that's the bottom.
It's like, no, I'm serious.
You need to add the other bricks to fang, you know?
And then there was like a pause and there was like this, and I think it's doable.
And so then actually I went back and thought about it a lot.
And I was like, hmm, is it doable?
Like, am I the crazy one or are they the crazy one?
Who's the crazy one here?
Like, who's nuts here?
And, you know, and that kind of pushed us to think about how do we change our comp philosophy?
How do we, if we wanted to go and get the best of the best out of Google, what does it require?
And we developed a new model where we're like actually the way to think about it is your market cap divided by number of employees.
That's how much money you can give away in terms of dilution.
And actually, we did calculate the number at that time.
And we're like wait, we're actually richer than Google in terms of you know how much dilution we can afford per engineer.
Because at that time, this was like, you know, before the Twitter downsizing.
So all the companies were oversized.
So we did the calculation.
It turned out that we actually can probably pay P95th percentile.
We did the math on P95th percentile for engineering.
And it was like, yeah, it's actually the math works out.
We moved all the compounds and we told them and we told the employees about it.
It's like, hey, we're paying you P95th, you know, and we can afford it.
And so that came out of that simple, you know, so these simple, you know, your trillion dollars, just add your acronym to the to FANG and so on.
They're silly and they're kind of crazy, but they do push you and you go back and think about hey, what is the fundamental reason from first principles that we couldn't do something like that?
Why couldn't we be a trillion?
What's the bottleneck from being a trillion or being part of Fang?
And then you think about it and you start zooming in on like, can we unblock that?
So it has helped us and has been a driving force, even though it's you know it's a little annoying, you know, you know it's like you know.
Hey mom dad, I got the A plus.
It's like, yeah, but we ranked second.
I was number two in the class.
Wait, so it was someone better than you?
Yeah.
Yeah for what it's worth.
When I joined the firm in 2019, the Series F of Databricks was the first deal I worked on, and I think the valuation was 6 billion.
Ben says to us, oh, well, it's going to be a $100 billion company.
And we're like, yeah, yeah, sure, Ben.
Lo and behold.
And I do all this work.
I'm like, what are you doing?
Like, $6 billion, $7 billion, doesn't matter.
I was right.
Yeah, that one you have proven to be right, yeah.
Still have ways to go for $2 trillion, but... Well, it...
The thing that you almost never get and Ali and I had this conversation the one time we did have a real acquisition offer on the company is You just don't get this good a market opportunity with this good an entrepreneur.
Like that's the rarest of rare things.
Like we see great entrepreneurs, but their market opportunity is limited.
And then we see you know companies that have a great market opportunity, but the entrepreneur is not big enough to fulfill that.
But this was a case where we had both.
Yeah, I remember actually the conversation that kind of flipped me.
The acquisition offer was on the table.
It was six times bigger than the valuation we had at the time.
And I had done the mistake of telling my co-founders.
Yeah, they were like, let's go.
They were like, we're done.
So everyone was like...
Stop the work.
Stop working.
Take your hands off the keyboards.
Nobody work anymore.
We're done here.
Right.
And let's count my money.
Like, you know, how much money do I have?
You know, what would you buy for that amount of money?
You know, so they were like completely like not doing anything.
And there's just this crazy gossip going around.
And then it was like they had told some of the exec and then they were calling each other every day.
Like, hey, what do you think?
Like, you know, I think he's he looked in a bad mood.
Do you think he's going to say no?
No.
It's like, what did he say?
Like he said this thing.
He said this once.
So there's just a lot of politicking going around and nobody was doing any work anymore.
And I was like, you know, maybe they're right.
Maybe we should just sell.
And I remember having that conversation with Ben.
And I think we were in a car, both of us.
And you know he says that he drops the F-bombs and he pisses people off and so on, and they don't take the feedback.
But actually he did exactly the radical candor thing with me, which is he said hey, you can do whatever you want.
I'll support you either case.
And actually, if you sell for this number, it's really great for me, me being done.
Like, we make a lot of money at A6NZ.
I'll pay the investors back many times over.
So honestly, if it's for me personally, that's probably the better option.
But I'm just thinking back.
I was CEO of CloudOpsWare.
And, you know, just the cards I were given, that company wasn't the company you have.
And when I look back, how often do you in life get a chance to even have a company like CloudCloud or OpsWare, let alone a Databricks?
And it's just such a freaking big market.
You can sell, you're going to make a lot of money and you'll be super successful in life.
But you know, if you're like me, you're going to look back the rest of your life thinking, you know I missed that one shot.
That was the one thing.
I should have taken it all the way.
And now I'll never know how far I could have taken it.
What could have been.
So do you want to live with that?
Or do you want to just have the money?
You know, I'll support whatever you want to do.
I really couldn't care less.
I really couldn't care less.
And I was like, okay, thanks.
Hang up.
We're never doing this.
We're done.
This is not happening.
What a pep talk.
Yeah.
So that's how we did it.
So it was excellent.
I think I also said, I guarantee you, you'll never have an idea this good again as long as you live.
This is the best idea you're ever going to have.
Yeah, yeah, yeah.
Well, an idea that also takes off and works, right?
Yeah.
Um.
So I want to tie one thing that you said in in all of that is you were company building um, but then also just sort of the calculus that founders, but also your employees, are making, and that's around comp.
Um, so in the early days you could afford to pay 95th percentile, right?
Um, Today, there's crazy AI talent wars going on.
We've talked about this a bunch throughout the summer.
And we know that you can bring the best talent in the house, right, to Databricks.
How do you keep them with all of this craziness going on?
Because now 95th percentile, I don't even know what that means.
Is that like you pay a billion dollars?
Yeah, exactly, exactly.
Yeah, the joke is, which company says we're P50th?
You know, we pay P50th.
Like, who does that?
There's no company that does that.
So how does...
The 75th percentile is the single biggest lie in Silicon Valley.
It's like a complete fabrication.
Probably, probably.
But, you know, I think that it is a crazy time with AI.
And I do think I feel bad.
I did actually an exit interview with someone this morning.
I feel bad for the kids right now because there's too much pressure on them.
They feel like, oh, they have to start companies.
And I've never actually had anything like this because every year I talk to the interns.
And, you know, I get questions about how do we build our own company?
You know, how do we succeed at Databricks and so on?
The last two years have just been crazy.
All the kids are like, when should I become a CEO?
When should I start my own company?
What's a good valuation?
Am I missing out?
If I do like an internship here for three months at Databricks, will I have wasted my opportunity in life?
And this is like the time for AGI.
And I could have like been one of the guys that does super intelligence.
And like, you know, how would you time that?
How was it for you?
How old were you?
When you were 22, what did you do?
And, you know, and so I do think it's kind of crazy times.
And I do think it's also exaggerated.
Like, you know, I don't think anyone's getting $100 million offers.
You know, I mean yes, there is like one, you know, characterai and so on, but I don't think it's actually true.
And it's also in the interest of CEOs.
You should know to say that hey, you know, you know people try to poach people from Databricks for a billion dollars.
And they said no, it's in our interest to say that right, because that kind of sets the bar at the billion.
And then any employee that gets an offer for half of that it's going to feel really insulted.
It's like when did I get a billion dollar offer?
I heard like on the news that the other people are getting a billion.
Um, So I do think that the most By the way, Sam used that in reverse on meta.
He's like, oh yeah, they offered all our guys $100 million.
And so the next guy who got the $15 million... Now I have to pay $100 at least, right?
That's like the smart move.
But I would say that look, you know, and not all startups have the valuation of their, So we're at 100 billion.
And, you know, with 10,000 employees, we actually can afford to actually pay significant.
And we do pay significant for the right talent.
But, you know, what did you do when you're smaller?
Like we were smaller at some point.
Well then it's talk about how big you are going to get and what the opportunity is and what you could do together and what it would be worth together.
But I think most people earlier in their career.
They really want to learn and they want to really feel that they can have impact.
So if you can really bring them in and you can sort of mentor them, you can stay close to them.
And as a CEO, you have huge power.
If you could just spend two minutes with, you know, a kid out of school, it's immense to them.
And you say, hey, you know, I'll even mentor you.
I'll help you.
Like, what do you want to do in five years?
I'm thinking about starting my own company actually in six months, you know, but I'll work at Databricks for 10 years, but in six months I would love to be a CEO.
So then you can say hey, I can coach you to.
You know, I know how the fundraising, I know the early days and so on.
And you can actually mentor a lot of them and that's actually worked a lot to them as well.
But in general, like help them be successful and help them build their careers.
And also if you've done it before, like we have, you can kind of calm them down a little bit and say hey, you have like a few decades, you know, don't worry about it.
It's like, it's not, you know, it's the FOMO and the pressure, you know, has to be kind of reduced.
And I think that's also calming.
They feel good about it.
Yeah.
Yeah.
I always say the best cure for starting your own company fever is to start your own company.
And that'll teach you.
It's not that easy.
By the way they come back, like after start companies.
Oftentimes they come back to Databricks and they're much more thankful and they understand.
And actually, I didn't mention this earlier when you asked about acquisitions.
My favorite acquisition, because I said to start with the people, right?
And then the product.
With the people, I love to hire people who have seen great at a big company.
Like, or I don't know if it's great, but they've seen process scale big company.
They've been at a Google, they've been at Amazon.
They understand the processes.
So they understand how to navigate a bureaucracy and work with it.
And they're not going to just be inundated by it.
But then they've gone on and done their own startup.
And um, and that's it really really hard right, it's like it's like extremely hard uh, trying to do everything yourself and you don't have any help and you know you're trying to do this in this crazy market and you're trying to compete with 100 million dollar offers when you have like nothing um, so that takes a certain amount of grit and it's really humbling, uh.
So i love the people that have done both of those.
They end up being actually the perfect employees at that works because they come in and they're really thankful, like hey, what these guys have done at that.
It's actually really really hard.
I tried it and I'm really good.
I was like one of the best at Google or somewhere.
And then I did my own startup and we absolutely failed.
And so, hey, show some respect here.
Like, you know, these guys know what they're talking about.
So those are great employees, actually.
So, you know, I think, keep a great relationship with people who leave your company, because they can boomerang back in a couple of years.
It's very hard to make these things work.
And it also requires a lot of luck.
I mean, I think one of the things people don't realize is a lot of things have to go right.
That should never go right.
And a lot of things will go wrong.
But like if you can grab your lucky moments, that's a rare, that's a rare thing.
Yeah, one way to prove that is if Databricks started in 2013, if we had started in 2012, you know, that rocky year, that difficult year, 2015 would have then happened in 2014, right?
To start the funds, we don't have the revenue.
But we were a cloud AI open source company.
Those things didn't take off in 2014.
So...
You know, even if we had to do the CEO change and all of that and I had become CEO a year earlier it just we were too early in the market.
The cloud hadn't taken off.
AI was not, nobody, that was not even a phrase.
AI meant robotics.
People use machine learning as a phrase.
And so company would have failed.
We wouldn't have had enough momentum.
There's not enough cloud, you know, TAM there to be had.
If we started the company in 2014, a year later instead, so a year later than we actually did, then we would have had our difficult year in 2016, right?
But by 2016, the cloud was starting to happen.
AI was starting to happen, you know.
So we would have done the fixes in 2017 and it would have been too late to the party.
And probably the hyperscalers would have taken it away.
You know our competitors were taking it away and we just wouldn't have get enough momentum to be able to succeed.
And that's timing of when we started.
So how did we clock it so well?
We had to wait for Matej to finish his PhD thesis.
That's it.
That was the whole thing.
So there's a lot of randomness and you got to get lucky.
And it was so on the edge as it was, that on the Series C, Jan had a handshake with Redpoint and Redpoint just stopped returning his calls to the point where the Series C was led by us, who also led the Series A, and NEA, who led the Series B, like we co-led the Series C, because nobody else would do it.
It was that bad. close to going under.
And more companies went even, right, that would be it.
Yeah, it was very close because we couldn't get funding for anyone.
It's just funding freezed up and nobody wanted to invest anymore.
So it was really a lifeline from A to Z. Yeah, we were just, you know, burning a lot of cash.
We weren't generating much revenue other than Spark Summit.
We had a lot of downloads.
We had a lot of downloads.
A lot of downloads.
And recurring conference revenue.
Yeah.
And recurring conference revenue.
How confident were you in that time when things were at their lowest?
Oh, I mean, I seriously considered taking the professor job at Berkeley because I, you know, I seriously thought this was going to be very, very hard to pull off.
You know, it's like you know.
I think the sentiment at Databricks was, or at least my sentiment was look, You win some things and you lose some things in life.
We created Apache Spark and we made it a worldwide sensation.
Everybody's downloading.
The downloads are through the roof.
We have this greatest conference.
Like, you know, thousands of people come to our conference.
It's awesome.
Let's go back.
Let's do it again.
Let's publish another paper and do those kinds of things.
We're just not business guys.
We just don't understand business.
You know, that's okay.
You know, we don't want to be business guys.
So that's kind of how I felt about it, right?
But what I knew was that, hey, you know... By the way, Matej went back and became a professor.
Like, all this stuff happened.
Yeah, Jan went back, you know.
But, you know, in 2015...
We knew that we had tried everything.
And by the way, PLG is something that we had tried very hard and it didn't work for us.
Actually, one of our biggest failures was PLG at Databricks.
Everybody kept telling us, PLG, PLG, PLG.
And we're like, okay, product-led growth.
And Amazon didn't.
You just swipe your credit card.
We don't need salespeople.
But so in 2015, I had to kind of like... Except cranny.
Exactly.
Yes, that is true.
Kudos to Mark.
So that year we had like formed some hypothesis that, you know, we have nothing to lose.
What if we just pivoted these things?
What if we went all in into B2B enterprise sales?
You know, because certainly PLG is not working.
You know, at 3 million ARR, that's not going to take you anywhere.
And, you know, and they're just taking our open source software.
So we have to have proprietary code around it, you know.
And yeah, the execs team are all PhDs.
So what if we bring in someone that doesn't have a PhD and see how it goes?
I never forget Arsalan going, we made the number.
I was like, you made a ridiculous number.
You made the number.
If you keep making that number, you're going to go bankrupt.
You didn't make the number.
You made a number that you set that was way too low.
Ben was very nice and complimentary in our board meetings that year, 2015.
We were in a bit of trouble.
Let's say it was very truth-seeking.
But yes, we had nothing to lose.
So we didn't know that we were going to succeed, but we had nothing to lose to make those big changes.
And we made them in 2016.
And it turned out those were the bottlenecks, you know, giving away your software for free, not having execs that have seen the movie before, like Ron who came in.
And, you know, just the PLG motion is not going to cut it.
So maybe we should just try.
We weren't certain that B2B would work, but we knew that PLG is not working for sure.
Yeah, well, another, like, I mean, you know, we got Ron.
I mean, like the fact that the first sales guy we hired was a sales savant, like a genius, shock.
I mean, like that never happens.
And he was a guy we didn't know.
Like we, like our talent team, like found him from some company we never heard of.
Yeah, French company, Axway.
And the only, really the only reason we hired him was because he was the only guy Cranny ever liked.
Like in all the sales guys he ever interviewed, he was like, this is the guy.
Wow.
Yeah, he is a new generation Mark Cranny T2.
But we just like stumbled into him.
Yeah, yeah, like unbelievable.
And, without Ron, very hard to see this company getting to where it got to.
So there's some luck involved in us even finding him.
But then he was phenomenal.
And also kudos to Jan, who actually led the search in 2015.
So you know.
But yeah, Ron was game changing for us.
But Ron was a very uncomfortable hire Because he did not have a PhD.
I did have an engineering degree.
Yeah, he does have an engineering degree from Stanford that helped a little bit.
But he's a sales, you know, true and true sales guy.
Like he's not a, you know, he's not one of these, he's a classic salesperson, right?
Who grew up in sales, even though he has an engineering degree.
So the comfortable thing would have been to pick someone.
And we had some candidates in the mix who were super technical, using the product, giving us feedback, but they probably would not.
And that would have been much more comfortable for us.
Yeah, Ron was uncomfortable.
He was a very uncomfortable hire and he made it very uncomfortable for us for many years and he still does.
But that's a lot of the key to the company.
Yeah.
It forces a customer focus that would be impossible to have without somebody that smart and crafty about getting his way.
I mean, just like unbelievable.
Yeah.
If you can keep also the original team together, that's important.
We're, you know, seven co-founders still.
Many of the co-founders, like, you know, you said data warehousing was a big push for us.
My co-founder, Reynold, was really the one that kind of pushed this.
Yeah, like well.
The contribution level from a large number of co-founders is unique in the industry.
I mean, you've got Patrick, you have Reynold, you have Matej, you have Arsalan.
I mean, like, it's crazy how much the original team contributes.
So the PhDs all contributed.
Arsalan really made the go-to-market work.
And he really made Ron work with the rest of the company.
That was super critical.
Matej continued doing lots of innovations over the years.
Patrick led all of engineering and big chunks of it.
And we've had other people.
We've been lucky to get such folks.
So hiring is critical and keeping the original talent, I think.
Those were some of the things.
Usually founders, usually only one of the co-founders contributes long-term.
And so to have you know, to have that going, and Jan's still on the board and Scott's still on the board.
I mean, like, it's very unusual.
Yep.
We have a lot more we can get into, but we're out of time.
So we'll leave it for future episodes of Boss Talk.
This is a great episode.
All right.
That was fun.
Thanks so much.
Thank you so much, guys.
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